Preprints

Louis Paulot, Calypso Herrera: Parallel American Monte Carlo Algorithm
In this paper we introduce a new algorithm for American Monte Carlo that can be used either for American-style options, callable structured products or for computing counterparty credit risk (e.g. CVA or PFE computation). Leveraging least squares regressions, the main novel feature of our algorithm is that it can be fully parallelized. Moreover, there is no need to store the paths and the payoff computation can be done forwards: this allows to price structured products with complex path and exercise dependencies. The key idea of our algorithm is to split the set of paths in several subsets which are used iteratively. We give the convergence rate of the algorithm. We illustrate our method on an American put option and compare the results with the Longstaff-Schwartz algorithm.

Past Talks

  • Bachelier Colloquium 2017, Métabief (France), 16.-21.1.2017
  • FWZ seminar, Freiburg (Germany),30.11.-2.12.2016
  • Post/Doctoral Seminar in Mathematical Finance, Zurich,25.10.2016, Convexity adjustment on terminal rate models
  • Imperial ETH Workshop on Mathemetical Finance 2016, Zurich, 26.-28.10.2016